1. Field of the Invention
The present invention relates to a method of analyzing molecular binding interactions at a sensing surface, and more particularly to the quality control of the resulting data describing the molecular interactions. The invention also relates to an analytical system including such a quality control as well as to a computer program for performing the method, and a computer system and computer program product, respectively, containing the program.
2. Description of the Prior Art
Analytical sensor systems that can monitor interactions between molecules, such as biomolecules, in real time are gaining increasing interest. These systems are often based on optical biosensors and usually referred to as interaction analysis sensors or biospecific interaction analysis sensors. A representative biosensor system is the Biacore® instrumentation sold by Biacore AB (Uppsala, Sweden) which uses surface plasmon resonance (SPR) for detecting interactions between molecules in a sample and molecular structures immobilized on a sensing surface. With the Biacore® systems it is possible to determine in real time without the use of labeling, and often without purification of the substances involved, not only the presence and concentration of a particular molecule in a sample, but also additional interaction parameters such as, for instance, the association rate and dissociation rate constants for the molecular interaction. The Biacore® system is currently used in life science research as well as in the drug discovery industry and in food analysis.
A typical output from the Biacore® and similar biosensor systems is a graph or curve describing the progress of the molecular interaction with time. This curve, which is usually displayed on a computer screen, is often referred to as a “sensorgram”. While it is possible for the operator of the biosensor instrument to assess the quality of the produced sensorgrams manually and discard any sensorgram of unacceptable quality, the current trend towards systems with ever increasing throughput and information density in the analyses performed puts a more and more heavy burden on the operator.
Accordingly, there remains a need in this field for improved methods and products for facilitating quality assessment in biosensor systems, especially where large sets of sensorgrams are produced.